Distribution of PCDD/F (polychlorinated dibenzo-p-dioxin and polychlorinated dibenzofuran) congeners at two electric arc furnaces (EAFs) in Taiwan is evaluated via intensive stack sampling and analysis. Two kinds of exhaust system in EAFs including stack system and shutter system are selected for measuring dioxin emissions. In addition, dioxin emissions during oxidation and reduction stages at EAF-A were characterized. Results indicate that the PCDD/F concentration of stack gas in EAF-A was 4.39 ng/N m3 while total Toxic Equivalent Quantity (TEQ) concentration was 0.35 ng I-TEQ/N m3. The PCDD/F concentration of stack gas in EAF-B was 2.20 ng/N m3 and the TEQ concentration was 0.14 ng I-TEQ/N m3. 1,2,3,4,6,7,8-HpCDF, OCDD and OCDF are the major contributors of the dioxin concentrations for two EAFs investigated and the percentage of PCDD/F in particulate phase increases as the chlorination level of the PCDD/F congener increases. The results obtained on gas/particulate partitioning of PCDD/Fs in flue gases prior to the APCD in EAFs indicate that more than 90% exists in particulate phase. In EAF-A, the PCDD/F concentration during oxidation stage is slightly higher than that measured during reduction stage, including the sampling points of CO converter outlet, prior to bag filter and stack. Majority of PCDD/Fs emitted from steel-making processes exists in particulate-phase (about 60–70%) at both EAFs investigated. 相似文献
Objectives: Nationally, animal–motor vehicle crashes (AVCs) account for 4.4% of all types of motor vehicle crashes (MVCs). AVCs are a safety risk for drivers and animals and many National Park Service (NPS) units (e.g., national park, national monument, or national parkway) have known AVC risk factors, including rural locations and substantial animal densities. We sought to describe conditions and circumstances involving AVCs to guide traffic and wildlife management for prevention of AVCs in select NPS units.
Methods: We conducted an analysis using NPS law enforcement MVC data. An MVC is a collision involving an in-transit motor vehicle that occurred or began on a public roadway. An AVC is characterized as a collision between a motor vehicle and an animal. A non-AVC is a crash between a motor vehicle and any object other than an animal or noncollision event (e.g., rollover crash). The final data for analysis included 54,068 records from 51 NPS units during 1990–2013. Counts and proportions were calculated for categorical variables and medians and ranges were calculated for continuous variables. We used Pearson’s chi-square to compare circumstances of AVCs and non-AVCs. Data were compiled at the park regional level; NPS parks are assigned to 1 of 7 regions based on the park’s location.
Results: AVCs accounted for 10.4% (5,643 of 54,068) of all MVCs from 51 NPS units. The Northeast (2,021 of 5,643; 35.8%) and Intermountain (1,180 of 5,643; 20.9%) regions had the largest percentage of the total AVC burden. November was the peak month for AVCs across all regions (881 of 5,643; 15.6%); however, seasonality varied by park geographic regions. The highest counts of AVCs were reported during fall for the National Capital, Northeast/Southeast, and Northeast regions; winter for the Southeast region; and summer for Intermountain and Pacific West regions.
Conclusions: AVCs represent a public health and wildlife safety concern for NPS units. AVCs in select NPS units were approximately 2-fold higher than the national percentage for AVCs. The peak season for AVCs varied by NPS region. Knowledge of region-specific seasonality patterns for AVCs can help NPS staff develop mitigation strategies for use primarily during peak AVC months. Improving AVC data collection might provide NPS with a more complete understanding of risk factors and seasonal trends for specific NPS units. By collecting information concerning the animal species hit, park managers can better understand the impacts of AVC to wildlife population health. 相似文献
Objectives: Both the National Vital Statistics System (NVSS) and the Fatality Analysis Reporting System (FARS) can be used to examine motor vehicle crash (MVC) deaths. These 2 data systems operate independently, using different methods to collect and code information about the type of vehicle (e.g., car, truck, bus) and road user (e.g., occupant, motorcyclist, pedestrian) involved in an MVC. A substantial proportion of MVC deaths in NVSS are coded as “unspecified” road user, which reduces the utility of the NVSS data for describing burden and identifying prevention measures. This study aimed to describe characteristics of unspecified road user deaths in NVSS to further our understanding of how these groups may be similar to occupant road user deaths.
Methods: Using data from 1999 to 2015, we compared NVSS and FARS MVC death counts by road user type, overall and by age group, gender, and year. In addition, we examined factors associated with the categorization of an MVC death as unspecified road user such as state of residence of decedent, type of medical death investigation system, and place of death.
Results: The number of MVC occupant deaths in NVSS was smaller than that in FARS in each year and the number of unspecified road user deaths in NVSS was greater than that in FARS. The sum of the number of occupant and unspecified road user deaths in NVSS, however, was approximately equal to the number of FARS occupant deaths. Age group and gender distributions were roughly equivalent for NVSS and FARS occupants and NVSS unspecified road users. Within NVSS, the number of MVC deaths listed as unspecified road user varied across states and over time. Other categories of road users (motorcyclists, pedal cyclists, and pedestrians) were consistent when comparing NVSS and FARS.
Conclusions: Our findings suggest that the unspecified road user MVC deaths in NVSS look similar to those of MVC occupants according to selected characteristics. Additional study is needed to identify documentation and reporting challenges in individual states and over time and to identify opportunities for improvement in the coding of road user type in NVSS. 相似文献
AbstractObjective: The number of e-bike users has increased significantly over the past few years and with it the associated safety concerns. Because e-bikes are faster than conventional bicycles and more prone to be in conflict with road users, e-bikers may need to perform avoidance maneuvers more frequently. Braking is the most common avoidance maneuver but is also a complex and critical task in emergency situations, because cyclists must reduce speed quickly without losing balance. The aim of this study is to understand the braking strategies of e-bikers in real-world traffic environments and to assess their road safety implications. This article investigates (1) how cyclists on e-bikes use front and rear brakes during routine cycling and (2) whether this behavior changes during unexpected conflicts with other road users.Methods: Naturalistic data were collected from 6 regular bicycle riders who each rode e-bikes during a period of 2 weeks, for a total of 32.5?h of data. Braking events were identified and characterized through a combined analysis of brake pressure at each wheel, velocity, and longitudinal acceleration. Furthermore, the braking patterns obtained during unexpected events were compared with braking patterns during routine cycling.Results: In the majority of braking events during routine cycling, cyclists used only one brake at a time, favoring one of the 2 brakes according to a personal pre-established pattern. However, the favored brake varied among cyclists: 66% favored the rear brake and 16% the front brake. Only 16% of the cyclists showed no clear preference, variously using rear brake, front brake, or combined braking (both brakes at the same time), suggesting that the selection of which brake to use depended on the characteristics of the specific scenario experienced by the cyclist rather than on a personal preference. In unexpected conflicts, generally requiring a larger deceleration, combined braking became more prevalent for most of the cyclists; still, when combined braking was not applied, cyclists continued to use the favored brake of routine cycling. Kinematic analysis revealed that, when larger decelerations were required, cyclists more frequently used combined braking instead of single braking.Conclusions: The results provide new insights into the behavior of cyclists on e-bikes and may provide support in the development of safety measures including guidelines and best practices for optimal brake use. The results may also inform the design of braking systems intended to reduce the complexity of the braking operation. 相似文献
Objective: The objective of this study was to conduct a comprehensive analysis of demographics, injury characteristics and hospital resource utilization of significant pediatric electric bicycle (e-bike) injuries leading to hospitalization following an emergency department visit in comparison to pediatric injuries caused by other traffic related mechanisms.Methods: A retrospective review of all pediatric traffic injury hospitalizations following an emergency department visit to a level I trauma center between October 2014 and September 2016 was conducted. Data regarding age, sex, number of computed tomography (CT) scans obtained, number of major procedures, length of hospital stay (LOS), Injury Severity Score (ISS), and number of injuries per patient were collected and compared between e-bike injuries and other traffic injuries.Results: Three hundred thirty-seven admissions were analyzed: 46 (14%) were due to e-bike injuries (29% of patients >12 years). Age, proportion of brain injuries, and use of CT were significantly increased compared to mechanical bicycle injuries (13.1?±?3.4 vs. 10.6?±?3.6, 13% vs. 3%, 1 [0–3] vs. 1 [0–1], P < .01, P = .03, P = .05). Age, LOS, and use of CT were significantly increased compared to injuries caused to automobile passengers (13.1?±?3.4 vs. 7.4?±?5.3, 1 [1–3] vs. 1 [1–2], 1 [0–3] vs. 0 [0–1], P < .01, P = .03, P = .01), as well as ISS and number of injuries per patient (P = .04, P < .01). Injuries caused by e-bikes were similar to injuries caused to pedestrians, except for age (13.1?±?3.4 vs. 8.5?±?3.7, P < .01). Multivariable analysis revealed a significant association between mechanism of injury and ISS, with increased ISS among e-bike injuries compared to mecahnical bike injuries (OR 2.56, CI 1.1–5.88, P = 0.03) and automobile injuries (OR 4.16, CI 1.49–12.5, (P < .01).Conclusion: E-bikes are a significant cause of severe injury in children compared to most other traffic injuries, particularly in older children. 相似文献
A cross-sectional study was undertaken to determine the prevalence of lower back pain (LBP) and its association with whole-body vibration (WBV) and manual materials handling (MMH). We studied 110 commercial vehicle drivers using a self-administered questionnaire and the VI-400Pro human vibration monitor. Prevalence of LBP was 66.4%. The percentage of drivers who had frequent manual handling of heavy loads was 45.5% and those who handled heavy loads in awkward postures accounted for 86.4%. Daily vibration A(8) averaged on the z axis was 0.25 (0.06) m·s?2 and at vector sum was 0.29 (0.07) m·s?2. Daily vibration exposures on the z axis, frequent manual handling of heavy loads and awkward posture during MMH were significantly associated with LBP. Drivers who are exposed to WBV and frequently handle heavy loads manually and with awkward postures probably have more LBP than drivers who are exposed to only one of these risk factors. 相似文献